适应一个任务叫Cross-type/task Transfer（CV叫Multi-task Learning）；适应一个领域（多用于CV）叫Cross...
将知识迁移到新环境中的能力通常被称为迁移学习（transfer learning），这就是本文将讨论的内容。在这篇...
As a result, applying deep learning techniques such as transfer learning to improve plant disease detection could be beneficial. ResNet50 with transfer learning is used to identify plant diseases in this study. ResNet50's performance is compared to VGG-16 and Inception V3, which were created ...
In 2022, we proposed a novel near-real-time, time-resolved 4D MRI framework1. It is an end-to-end DL-formulation and based on the same acquisition scheme proposed by Siebenthal et al.13 but removes the active search for data slices by learning the relation between navigator and data ...
Transfer learning is a deep learning (DL) method that allows the use of a pretrained model with a new dataset. The new data must be similar enough to the original data so the learned features in the model weights apply well. If this is the case, then transfer learning can greatly red...
We provide many example codes in the directory examples, which is divided by learning setups. Currently, the supported learning setups include: DA (domain adaptation) TA (task adaptation, also known as finetune) OOD (out-of-distribution generalization, also known as DG / domain generalization)...
Transfer learning uses pre-trained models from one machine learning task or dataset to improve performance and generalizability on a related task or dataset. Transfer learning is a machine learning technique in which knowledge gained through one task or dataset is used to improve model performance on...
【李宏毅2020 ML/DL】P85 Transfer Learning 我已经有两年 ML 经历,这系列课主要用来查缺补漏,会记录一些细节的、自己不知道的东西。 本节内容综述 要做一项任务,但是数据不直接与任务相关。这就涉及到了迁移学习。在现实生活中,我们其实不断在做“迁移学习”。
零样本学习（Zero-shot Learning）：在迁移学习中，零样本学习是指使用预训练模型在没有新任务数据的情况...
滚动轴承故障 滚动轴承中的局部故障可能发生在外圈、内圈、保持架或滚动体中。 当滚动体撞击外圈或内圈上...